The Ethical Implications of AI in Decision -Making Systems

Artificial Intelligence (AI) has become increasingly integrated into decision-making systems across various sectors, including healthcare, finance, and criminal justice. While AI offers efficiency and scalability, its ethical implications raise significant concerns. This article explores the biases inherent in AI algorithms, often stemming from flawed or unrepresentative training data, which can perpetuate discrimination and inequality. For instance, facial recognition systems have demonstrated racial and gender biases, while predictive policing tools may disproportionately target marginalized communities. The article also examines the 'black box' problem, where AI systems make decisions without transparent reasoning, making accountability challenging. The lack of explainability undermines trust and complicates regulatory oversight. Furthermore, the delegation of critical decisions to AI raises philosophical questions about autonomy and human agency. Should AI determine parole eligibility or medical diagnoses without human intervention? To address these issues, the article proposes a multidisciplinary approach involving ethicists, technologists, and policymakers. Strategies include improving dataset diversity, developing explainable AI (XAI) frameworks, and establishing robust legal frameworks to govern AI deployment. The goal is to harness AI's potential while safeguarding human rights and societal values.

کلیدواژه ها:

Ethical AI ، Algorithmic Bias ، Explainable AI ، Decision-Making Systems